英文标题：
《A Theory of Information overload applied to perfectly efficient
financial markets》
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作者：
Giuseppe Pernagallo and Benedetto Torrisi
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最新提交年份：
2019
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英文摘要：
Before the massive spread of computer technology, information was far from complex. The development of technology shifted the paradigm: from individuals who faced scarce and costly information to individuals who face massive amounts of information accessible at low costs. Nowadays we are living in the era of big data and investors deal every day with a huge flow of information. In the spirit of the modern idea that economic agents have limited computational capacity, we propose an original model using information overload to show how too much information could cause financial markets to depart from the traditional assumption of informational efficiency. We show that when information tends to infinite, the efficient market hypothesis ceases to be true. This happens also for lower levels of information, when the use of the maximum amount of information is not optimal for investors. The present work can be a stimulus to consider more realistic economic models and it can be further deepened including other realistic features present in financial markets, such as information asymmetry or noise in the transmission of information.
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中文摘要：
在计算机技术大规模传播之前，信息远非复杂。技术的发展改变了这种模式：从面对稀缺和昂贵信息的个人，转变为面对以低成本获取大量信息的个人。如今，我们生活在大数据时代，投资者每天都在处理巨大的信息流。本着经济主体计算能力有限的现代理念，我们提出了一个原始模型，使用信息过载来显示过多的信息会导致金融市场偏离传统的信息效率假设。我们发现，当信息趋于无限时，有效市场假说不再成立。这种情况也发生在信息水平较低的情况下，因为对投资者而言，使用最大数量的信息并非最佳选择。目前的工作可以促进考虑更现实的经济模型，还可以进一步深化，包括金融市场中存在的其他现实特征，如信息不对称或信息传输中的噪音。
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分类信息：

一级分类：Quantitative Finance 数量金融学
二级分类：Statistical Finance 统计金融
分类描述：Statistical, econometric and econophysics analyses with applications to financial markets and economic data
统计、计量经济学和经济物理学分析及其在金融市场和经济数据中的应用
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